Token Classification
Transformers
PyTorch
Safetensors
Spanish
xlm-roberta
text-classification
biomedical
clinical
spanish
XLM_R_Galen
Eval Results (legacy)
Instructions to use IIC/XLM_R_Galen-meddocan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/XLM_R_Galen-meddocan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="IIC/XLM_R_Galen-meddocan")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIC/XLM_R_Galen-meddocan") model = AutoModelForSequenceClassification.from_pretrained("IIC/XLM_R_Galen-meddocan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from IIC/XLM_R_Galen-meddocan: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/IIC/XLM_R_Galen-meddocan/resolve/91208cb83f1614f74b932c0d007da3454487964c/tokenizer.json
- Command line
-
hf download hf://IIC/XLM_R_Galen-meddocan@91208cb83f1614f74b932c0d007da3454487964c/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/IIC/XLM_R_Galen-meddocan/resolve/91208cb83f1614f74b932c0d007da3454487964c/tokenizer.json
17.1 MB
- Xet hash:
- 9ac4706cc3c90313627b45bc62e236777b117bb725050d0c71deb8f507d9d7e0
- Size of remote file:
- 17.1 MB
- SHA256:
- 8a3d8b13e81f1324c05ee2a010c2f9b49f4ceb5887da444843b6dddd035d8701
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.